What is Explainable Artificial Intelligence (XAI)?
Today, there are scores of machine learning algorithms in using that sense, think, and act in a range of different applications and techniques. Yet many of these algorithms are still considered “black boxes,” as it offers little if any insight into how they reached their outcome. Explainable AI is a way to develop machine learning techniques and technologies that produce more explainable models while maintaining prediction accuracy.
Comparing Explainable AI with Traditional AI
Explainable Artificial Intelligence achieves more accuracy as compared to traditional AI, and they seem to be more exploratory.
Explainable Artificial Intelligence Applications
AI that is accountable, confirmable, and see-through will be demanding to establish confidence in the technology and will encourage broader adoption of machine learning and profound learning ways and tools. Enterprises will adopt explainable AI as a need or best practice before commencing on widespread.
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